An analysis of litter nitrogen dynamics using artificial soils across a gradient of forest soil disturbances
Bibliographic record
Abstract
The release of nutrients from a standard litter is often assumed to be solely a function of its decomposition rate. We tested whether nitrogen release would also be influenced by soil attributes affected by disturbance, such as interactions with soil microflora. Changes in nitrogen contents of decaying litter (Populus balsamifera) were compared across soil compaction and organic matter removal treatments in central British Columbia, using artificial materials to isolate litter bags from contact with forest floors or mineral soil. After 30 mo, nitrogen content of litter was only slightly higher on artificial soils than actual soils, suggesting that most nitrogen had been lost by leaching. A significant interaction, however, was detected in leaf nitrogen content between organic matter removal and soil compaction treatments that was not found on the artificial soils. This difference in nitrogen release led to a range in C:N ratios of 28 to 32 (from an initial C:N ratio of 52) for leaves at 1.5 g (70% mass loss). The differences in nitrogen release were relatively small and will perhaps be less important than other effects of soil disturbance (such as changes in litter quality) on nitrogen cycling. Key words: Nitrogen, decomposition, litter bag, translocation, compaction, forest floors
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".